Multimodal measurement of hand function with the SensorE Exoskeleton: a validation study

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Wearable Sensors

Background:

• Strokes frequently result in persistent upper extremity impairments.
• Current clinical assessments for hand function lack objectivity and sensitivity.
• Objective, multimodal measurement tools for hand function are scarce.

Purpose of the Study:

• To design and validate the SensorE Exoskeleton (SEE), a novel wearable device.
• To simultaneously quantify finger flexion and applied fingertip force.
• To provide a sensitive alternative to subjective clinical assessments for hand function.

Main Methods:

• The SEE integrates flex and force sensors into a lightweight wearable design.
• Thirty healthy participants performed graded finger tasks guided by a GUI.
• SEE measurements were validated against a motion capture system and a load cell.

Main Results:

• SEE reliably distinguished between different levels of finger movement and force (p < 0.05).
• Flex sensor data showed strong correlation with motion capture (|r| > 0.7).
• Force sensor data correlated well with load cell measurements (|r| > 0.7) with low relative errors.

Conclusions:

• The SEE offers accurate, objective, and sensitive tracking of finger flexion and force.
• This multimodal wearable device has potential as a novel functional assessment tool in rehabilitation.
• Future validation in stroke and other patient populations is warranted.